We build AI agents around specific workflows, connected to your tools, grounded in your knowledge, and handing off to people where judgment matters.
Recurring tasks run across your tools on their own, with clear limits and a person looped in when something needs a call.
Agents handle routine requests, gather the details, and route anything complex to the right person with context attached.
Research organized, drafts prepared for review, and company knowledge pulled into everyday work.
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We track time saved, quality, cost, and what still needs a person. On average, up to 75% of a workflow ends up automated.
Define the job
Agree on the task, the users, the inputs and what “done well” looks like before we build.
Test on real examples
Quality and failure cases are checked against examples pulled from your actual work.
Connect what matters
Integrations are chosen around the task and the systems your team already uses.
Set the boundaries
Every agent has defined data access, permitted actions and a named owner.
Reuse what works
Proven steps are reused across agents and retested in each new context.
Make handoffs visible
Every handoff between tools, agents and people is explicit and logged.
Measure outcomes
Completion rate, time saved, review load and cost are tracked for every workflow.
Improve on evidence
Approaches are compared on real work, and only what proves better ships.
